Top Tech Jobs & Startup Jobs in NYC, NY

Manage a high-volume portfolio of mid-market SaaS customers using scalable engagement, onboarding, training, automation, and digital communications. Monitor health and usage data to identify churn risks, expansion opportunities, and adoption trends. Lead targeted customer meetings, promote AI and analytics use cases, coordinate with Sales, Support, and Product, and develop reusable customer success playbooks and resources.

Build and maintain scalable security platforms, automation, APIs, detections, and internal tooling for a cloud-native SaaS environment. Secure AI applications, LLM services, identities, SaaS platforms, cloud infrastructure, and APIs. Develop controls against prompt injection, data leakage, model misuse, and excessive permissions while supporting vulnerability management, incident response, threat modeling, and security operations.

Manage strategic customer accounts for Sigma Computing, helping users maximize analytics platform value and improving net dollar retention. Responsibilities include developing success plans, identifying upsell and cross-sell opportunities, reducing churn, advocating for customer needs, delivering training, and guiding customers on analytics and business intelligence solutions. The role requires strong communication, analytical problem-solving, SaaS customer success experience, and familiarity with SQL, ETL, data visualization, and cloud analytics platforms.

Technical Writing Interns will test product features and create clear, accurate documentation, tutorials, examples, release notes, diagrams, screenshots, and dynamic content. They will collaborate with engineers, designers, product managers, and writers; participate in planning and bug bashes; analyze customer feedback and metrics; publish content through a docs-as-code workflow; and complete an end-to-end documentation project during a 12-week, in-person internship.

Conduct original AI/ML research in search, recommendations, NLP, and agentic workflows; prototype and productionize AI systems; address AI, analytics, and data-app UX challenges; and help build scalable infrastructure for model experimentation, training, and evaluation. The role requires a current AI/ML PhD student with strong machine learning expertise and knowledge of the full ML lifecycle.

Software Engineering Interns will design, prototype, implement, test, and deploy production features for Sigma’s cloud analytics platform. They will collaborate with engineers, product managers, designers, sales, and users; build scalable frontend and backend systems; optimize performance; document work; and use customer metrics to improve development decisions. The internship is full-time, 12 weeks, and in person in San Francisco or New York.

Provides post-sales technical expertise for Sigma customers by designing and implementing business intelligence solutions, advising on analytics best practices, performance, security, embedded analytics, APIs, and data integrations. Partners with customers, Product, Engineering, and GTM teams; troubleshoots deployed solutions, documents implementations, captures product feedback, identifies expansion opportunities, supports renewals, and develops customer references. Requires extensive customer-facing BI experience and up to 50% travel.

Leads enterprise customer success strategy, operations, and CSM teams to drive customer value, adoption, retention, expansion, and growth. Develops scalable post-sales processes, monitors customer health and business metrics, mentors high-performing teams, manages escalations, and builds feedback loops with Sales, Product, Engineering, and Support. Owns NDR and quarterly objectives while driving organizational change, customer advocacy, and referenceability.

Own revenue operations for a rapidly scaling B2B SaaS sales organization. Responsibilities include operating rhythms, QBRs, annual planning, strategic diagnostics, pipeline analysis, AI-enabled workflow automation, and advising senior sales leadership. The role requires building scalable systems, identifying risks early, improving operational efficiency, and partnering directly with VP-level stakeholders.

Lead technical presales by discovering customer needs, building and presenting customized BI demos and prototypes, responding to RFPs/RFIs, supporting integrations and data migrations, and managing multiple customer engagements to drive adoption and sales.